Advances in wireless and/or wired telecommunications are rapidly increasing the utilization of IMS user endpoint devices (UEs) that facilitate communication between users. Typically, a master database, such as a Home Subscriber Server (HSS) in 3GPP architecture, is utilized to store subscription-related information (e.g., subscriber profiles) and registration information associated with the IMS user endpoint devices (UEs). Moreover, the HSS can perform authentication and authorization of the user and can provide information about the subscriber's location and/or IP information. In addition, the HSS provides services to other call processing servers within the communication network, such as Call Session Control Functions (CSCF), application feature servers in 3GPP IP Multimedia Subsystem (IMS) and Long Term Evolution (LTE) networks.
With evolution and growing popularity of wireless and/or wired communication, the HSS can grow to a very large server complex, which can experience various overload conditions. In one example, a faulty server or network connectivity can reduce the available capacity for the HSS. In another example, other portions of the Next Generation Network (NGN) can experience fault recovery resulting in a large number of user equipments (UEs) to flood the NGN core network with initial registration requests. Many conditions including the above examples can cause the HSS to enter an overload condition.
Conventionally, the HSS utilizes an overload protection design that randomly rejects or drops requests from its clients. In particular, when an overload threshold is reached, the conventional system will kick in the associated overload protection policy, which results in rejection or dropping of one or more processing requests. However, when HSS randomly rejects or drops some requests in overload condition, it can drop a second or third Diameter request from a call processor processing a single Session Initiation Protocol (SIP) request, wherein the first or second request has already been processed. To this end, the SIP request fails and the HSS processing for the first and second Diameter request results in a complete waste of the stressed HSS resources. Thus, the traditional approach for overload protection within the HSS, wherein requests are randomly dropped and/or rejected is inefficient and can negatively impact performance and even aggravate the overload condition.